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AI123AI ModelsgoogleGemini 2.5 Pro
Gemini 2.5 Pro

Gemini 2.5 Pro

google

Gemini 2.5 Pro is Google’s state-of-the-art AI model designed for advanced reasoning, coding, mathematics, and scientific tasks. It employs “thinking” capabilities, enabling it to reason through responses with enhanced accuracy and nuanced context handling. Gemini 2.5 Pro achieves top-tier performance on multiple benchmarks, including first-place positioning on the LMArena leaderboard, reflecting superior human-preference alignment and complex problem-solving abilities.

Modalities
TT
Input / output price
$1.25/$10per 1M tokens
Context
1.0M
Released
2025-06-17
PricingArtificial AnalysisDesign ArenaRelated Models

Pricing

Usage prices in USD. Token rates are per one million tokens; other billing units are shown with each charge.
InputOutputCache readCache writeWeb search
$1.25/ 1M tokensOver 200K: $2.50 / 1M tokens$10.00/ 1M tokensOver 200K: $15.00 / 1M tokens$0.13/ 1M tokensOver 200K: $0.25 / 1M tokens$0.38/ 1M tokens$0.014/ request

Artificial Analysis

Explore rankings
16.1

Intelligence index

Outperforms 47% of compared models

33.3

Coding index

Outperforms 33% of compared models

1.6

Agentic index

Outperforms 26% of compared models

Design Arena

Elo scores and win rates across design and agent tasks.

Category performance

1,000-1,500 Elo
3D: 1076; Code Categories: 1150; Data Visualization: 1222; Game Development: 1111; UI Component: 1134; Website: 11653D1076 EloCode Categories1150 EloData Visualization1222 EloGame Development1111 EloUI Component1134 EloWebsite1165 Elo

Model Arena

Data Visualization

1222Elo

Win rate 68.2%

UI Component

1134Elo

Win rate 57.5%

Website

1165Elo

Win rate 58.4%

Code Categories

1150Elo

Win rate 57.5%

Game Development

1111Elo

Win rate 54.2%

3D

1076Elo

Win rate 50.6%

How Design Arena works

Related Models

Gemini 4 Argon

Gemini 4 Argon

google

Gemini 4 Argon is Google's flagship reasoning model, built for complex software engineering, deep mathematical and scientific problem solving, and autonomous multi-step agents. Google trained it to keep context across long, multi-step tasks and to turn long documents mixing text, tables, charts and images into a single grounded output. It leads the Vals Index across finance, legal, coding and tax work, and supports long decode of up to 1M output tokens in a single response.

Context
1.0M
Max output
943.7K
Released
2026-10-13
Input
$2/M
Output
$10/M
Cache read
$0.1/M
Gemini 3.8 Flash

Gemini 3.8 Flash

google

Gemini 3.8 Flash is Google's most intelligent Flash model with significant gains from 3.7 Flash across software engineering, agentic tasks, and multi-step reasoning.

Context
1.0M
Max output
65.5K
Released
2026-09-02
Input
$0.825/M
Output
$4.13/M
Cache read
$0.083/M
Gemini 3.7 Flash

Gemini 3.7 Flash

google

Gemini 3.7 Flash is a multimodal model from Google for fast agentic workflows, coding, and complex multi-step reasoning. It is designed for tasks that require responsive performance and reliable multi-step problem solving.

Context
1.0M
Max output
65.5K
Released
2026-08-13
Input
$0.75/M
Output
$3.75/M
Cache read
$0.075/M
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